Ph.D Students

In Progress

  1. Vivek V.P: Reinforcement learning, team theory, Joined January 2018

  2. Soumyajit Guin: Reinforcement learning algorithms, Joined August 2018

  3. Ashish Srivastava (ERP; joint guidance with Prof. M.Narasimha Murty and Dr. S.Rakshit): Joined August 2019

  4. Joji Joseph (RBCCPS; joint guidance with Prof. Bharadwaj Amrutur): Joined August 2019

  5. Lakshmi Mandal: Joined August 2020

  6. Krishna Chaitanya Sudapalli (RBCCPS; joint guidance with Prof. Bharadwaj Amrutur): Joined August 2020

Former Students

  1. D. Raghuram Bharadwaj: Reinforcement Learning Algorithms for Off-Policy, Multi-Agent Learning and their Applications to Smart Grids, graduated, 2022

  2. Sindhu P.R.: Algorithms for Challenges to Practical Reinforcement Learning, graduated, 2021

  3. Chandramouli K., Algorithms for Stochastic Optimization, Statistical Estimation and Markov Decision Processes, graduated 2020

  4. Indu John: Decision Making under Uncertainty: Reinforcement Learning Algorithms and Aaplications in Cloud Computing, Crowdsourcing and Predictive Analytics, graduated 2020

  5. Vinayaka G. Yaji: Stochastic Approximation with Set-Valued Maps and Markov Noise: Theoretical Foundations and Applications, graduated 2018

  6. Prasenjit Karmakar: Stochastic Approximation with Markov Noise: Analysis and Applications in Reinforcement Learning, graduated 2018

  7. Arunselvan Ramaswamy: Stochastic Approximation Algorithms with Set-Valued Dynamics: Theory and Applications, graduated 2017

  8. Ajin George Joseph: Optimization Algorithms for Deterministic, Stochastic and Reinforcement Learning Settings, graduated 2017

  9. Ranganath B.N.: Scalable Sparse Bayesian Nonparametric and Matrix Tri-factorization Models for Text Mining Applications, graduated 2017

  10. K.J. Prabu Chandran: Feature Adaptation Algorithms for Reinforcement Learning with Applications to Wireless Sensor Networks and Road Traffic Control, graduated 2016

  11. Chandrashekar Lakshmi Narayanan: Approximate Dynamic Programming and Reinforcement Learning - Algorithms, Analysis and An Application, graduated 2016

  12. Lakshmanan K : Online Learning and Simulation based Algorithms for Stochastic Optimization, graduated 2013.

  13. Prashanth L.A : Resource Allocation under Uncertainty: Studies in Vehicular Traffic Control, Service Systems, Sensor Networks and Mechanism Design, graduated 2013.

  14. H.L. Prasad : Algorithms for Stochastic Games and Service Systems, graduated 2013.

  15. Vivek Kumar Mishra : Simulation Based Methods for Optimization, graduated 2012.

  16. Mohammed Shahid Abdulla : Simulation Based Algorithms for Markov Decision Processes and Stochastic Optimization, graduated 2008.

  17. Ambedkar Dukkipati (joint guidance with Prof. M. Narasimha Murty) : On Generalized Measures of Information with Maximum and Minimum Entropy Prescriptions, graduated 2007.

  18. Viswanath Pulabaigari (joint guidance with Prof. M. Narasimha Murty) : Pattern Synthesis Techniques and Compact Data Representation Schemes for Efficient Nearest Neighbor Classification, graduated 2005.